A curated guide analyzing modern code sandboxing solutions, this repository addresses the critical need for secure code execution in AI applications and user-programmable platforms. It empowers developers, architects, and leaders to navigate the complex landscape of sandboxing technologies by detailing their inherent trade-offs between security, performance, and compatibility.

How It Works

Sandboxing approaches are categorized into four main types: hardware-level Micro-Virtual Machines (MicroVMs) like Firecracker, application kernels such as gVisor that intercept system calls, lightweight Language Runtimes like WebAssembly and V8 Isolates, and namespace-based Containerization exemplified by Docker/OCI. Each technology offers distinct balances of security isolation strength, startup speed, resource overhead, and compatibility, catering to diverse use cases from edge computing to full development environments.

Highlighted Details

• MicroVMs provide robust hardware-enforced isolation with significantly faster startup times than traditional VMs, effectively bridging the gap between VMs and containers.
• Application Kernels offer enhanced security over standard containers without requiring hardware virtualization, though they may introduce some performance overhead.
• Language Runtimes deliver the fastest startup and lowest resource consumption but are the most restrictive in terms of compatibility and functionality.
• Containerization is highly performant and compatible but shares the host kernel, posing security risks, particularly when executing untrusted code.
• The guide features in-depth profiles of platforms like e2b, Daytona, and microsandbox, alongside a decision framework to aid selection based on security needs, workload type, hosting preferences, and AI-specific requirements.

Maintenance & Community

This document is presented as a "living document," actively encouraging community contributions through GitHub issues or pull requests. This collaborative approach aims to maintain accuracy and comprehensiveness as the field of code sandboxing rapidly evolves.

Licensing & Compatibility

The listed sandboxing projects exhibit a range of licensing models, from permissive Apache-2.0 (e.g., e2b, microsandbox) to copyleft AGPL-3.0 (e.g., Daytona), and proprietary licenses for SaaS offerings. Compatibility varies significantly based on the underlying technology—MicroVMs, containers, or language runtimes—impacting integration into different development and deployment ecosystems.

Limitations & Caveats

No single sandboxing technology is universally optimal; each involves inherent trade-offs. MicroVMs offer superior isolation but may incur higher resource overhead and latency compared to containers. Containerization, while popular for its performance and compatibility, carries risks due to the shared host kernel, with misconfigurations being a frequent source of security incidents. Language runtimes provide speed but are highly limited. The sandboxing landscape is dynamic, necessitating ongoing evaluation.